Difference between revisions of "Viewpoint: a pragmatic approach to constructing a minimum data set for care of patients with HIV in developing countries"

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Implementation of a standardized [[Designated record set|minimum data set]] for the management of HIV+ patients in developing countries offers an opportunity to improve care of individual patients as well as populations.
 
Implementation of a standardized [[Designated record set|minimum data set]] for the management of HIV+ patients in developing countries offers an opportunity to improve care of individual patients as well as populations.
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==Related Articles==
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[[Cooking up an open source EMR for developing countries: OpenMRS – a recipe for successful collaboration]]
  
 
== References ==
 
== References ==

Latest revision as of 22:42, 7 November 2015

Minimum data set may facilitate care of HIV+ patients in developing countries

It’s commonly assumed that information technology has limited applicability in developing countries. However, infection with the human immunodeficiency virus (HIV) requires the type of comprehensive, highly managed care that electronic medical records (EMRs) are designed to facilitate. Development of a minimum data set that supports local care management and monitoring as well as national epidemiological and data sharing initiatives would significantly improve care of HIV+ persons in developing countries. Tierney et al. describe key considerations and challenges to be addressed in this endeavor.

Introduction

Ideally, a minimum data set would balance the resources required for data collection and management against the benefits of collecting a piece of data. The EMR concept described is based on three assumptions:

  1. clinics that provide HIV also provide comprehensive care to the local population; # HIV clinics provide comprehensive prevention and treatment services to HIV+ patients and their families
  2. data collected during individual outpatient visits would be used to manage HIV care locally, regionally, and nationally
  3. the data used by clinic managers and national administrators represents a subset of the data used by local providers in day-to-day practice

Data user groups include clinic management staff; clinicians and allied health staff; practice managers; district, regional, and national program administrators; and funding agencies. To be useful to such a wide range of users, the EMR must support the terminology that clinicians use and understand as well as any international coding systems (e.g., ICD-9, CPT-4) used by national program administrators. Clinicians will want some free text capability, but most entries should be entered as numeric and coded categorical data in a standard format (e.g., HL7) to facilitate summarization and sharing of data with other data management systems.

In the minimum data set the data to be collected is organized into two categories:

  1. registration, scheduling, and practice management data
  2. clinical data

The registration category includes a unique patient identifier, patient name and address, visit date, site of care, patient demographics, a family identifier, unique provider identifiers, payment program identifiers, and charges and payments. The clinical category includes the medical history; physical examination; diagnostic tests ordered and results; treatment-related data such as drugs prescribed, procedure, physical therapy, and counseling; visit diagnoses; medication adherence; clinic referral and/or hospitalization; and death date and cause. The minimum data set should be based upon the comprehensive examination as it is provided locally. Those developing an EMR should take into account other data needs unique to the locality and design a tool that will accommodate expected future needs.

Comment

Implementation of a standardized minimum data set for the management of HIV+ patients in developing countries offers an opportunity to improve care of individual patients as well as populations.

Related Articles

Cooking up an open source EMR for developing countries: OpenMRS – a recipe for successful collaboration

References

  1. http://www.ncbi.nlm.nih.gov/pubmed/16501175